[SOLVED] Project Guideline: Forecasting Demand Forecasting for
[SOLVED] Project Guideline: Forecasting
Demand Forecasting for the Inner-city Health Center
Inner City Health Center is a federally funded health clinic that serves the needs of the inner-city poor. Currently the center is at the end of third-year operation and is preparing its staffing plan for the upcoming year. The federal government requires that the center prepare a budget request each year. The request is based largely on the forecast of the # of Patient Visit for specific services during the next year.
The health center administrator has in the past tried using the last month’s # of Patient Visit and has also tried using the average of all historical data to predict the next period’s # of Patient Visit for the center. Neither of these two techniques has proven satisfactory due to complicated month to month data pattern. They are currently seeking outside helpers to forecast the # of patient visit for the upcoming January year 2016.
The # of patient visit each month in the preceding three years (including the current year) is available in the following Table.
Table. Emergency Service Demand for the Inner-city Health Center
Month
# of patient Visit
Year 2013
Year 2014
Year 2015
Jan.
251
382
537
Feb.
317
462
574
Mar.
329
464
652
Apr.
399
529
682
May
461
619
729
June
536
659
747
July
495
597
673
Aug.
455
548
676
Sept.
411
469
665
Oct.
343
490
571
Nov.
286
474
605
Dec.
288
375
562
Assignment: You may copy and paste the data to your Excel Spreadsheet. I would also suggestion that you re-arrange data into a 2-dimension table (Months, #of patient visit). To do so will make your job easier.
• Forecast
• Use a 3-month Moving Average Method to forecast the # of the emergency visit from April 2013 to January 2016.
• Use a Linear Projection Forecast Method to forecast the # of the emergency visit from January 2013 to January 2016.
• Use an Exponential Smoothing Forecast Method, with = 0.3, to forecast the # of the emergency visit from April 2013 to January 2016. Assume that initial forecast for March 2013 is 400.
• Plot One (nice) Chart for Data Series over time (Jan 2013 to Jan 2016):
• the historical data series,
• the data series of forecasts obtained in 1a), 1b) and 1c).
• Can you tell which of the three forecast methods is the best based on the chart?
• Use one of forecast Error Measurements, either MAD, or MSE, or MAPE (you choose) to determine which of the forecasts from 1a), 1b) or 1c) provides the best (smallest) forecasting error summary from the given historical data set.
• It is important to point out that error comparison of different forecast methods should be done on a Consistent Base. That is, the forecast error comparison for different forecast methods is meaningful only when we compare errors from the Same Range of forecasts.
• For the Exponential Smoothing forecast obtained in 1c), use Tracking Signal to monitor the forecast results and draw a conclusion on whether or not the forecasts are Biased, assume C = 3, and -C = -3 to be the control limits of the tracking signal method.
• Use the same Forecast Error Measurement you used in question 3), find the best smoothing parameter (i.e. the that leads to the smallest forecast error) of Exponential Smoothing Forecast Method.
• For the given historical data set,
• Based on the data pattern of the three-year data set, one can argue that the forecast methods used in 1a)-c), or, in general, we may conclude that Moving average, Linear Trend Project, and Exponential Smoothing Method should not be good Forecasting methods for the given data set. Can you Explain why?
• Propose Your Own Forecast Method (Other than the Moving Average, Linear Trend Project, and Exponential Smoothing Method) that might be better than the forecast methods 1a) - 1c). Use the Forecast Method proposed to do forecasts from May 2013 to December 2016.
• Use the Same Forecast Error Measurement as you used in part 3) to calculate forecasting error from your method, and then to compare the forecasting error with the results you obtained in 1a)- c). Is your method better?
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